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Titlebook: Artificial Intelligence and Security; 6th International Co Xingming Sun,Jinwei Wang,Elisa Bertino Conference proceedings 2020 Springer Natu

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發(fā)表于 2025-3-21 19:29:58 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Artificial Intelligence and Security
期刊簡(jiǎn)稱6th International Co
影響因子2023Xingming Sun,Jinwei Wang,Elisa Bertino
視頻videohttp://file.papertrans.cn/163/162277/162277.mp4
學(xué)科分類Communications in Computer and Information Science
圖書封面Titlebook: Artificial Intelligence and Security; 6th International Co Xingming Sun,Jinwei Wang,Elisa Bertino Conference proceedings 2020 Springer Natu
影響因子.The 3-volume set CCIS 1252 until CCIS 1254 constitutes the refereed proceedings of the 6th International Conference on Artificial Intelligence and Security, ICAIS 2020, which was held in Hohhot, China, in July 2020. The conference was formerly called “International Conference on Cloud Computing and Security” with the acronym ICCCS...The total of 178 full papers and 8 short papers presented in this 3-volume proceedings was carefully reviewed and selected from 1064 submissions. The papers were organized in topical sections as follows:..Part I: artificial intelligence;..Part II: artificial intelligence; Internet of things; information security;..Part III: information security; big data and cloud computing; information processing..
Pindex Conference proceedings 2020
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書目名稱Artificial Intelligence and Security影響因子(影響力)




書目名稱Artificial Intelligence and Security影響因子(影響力)學(xué)科排名




書目名稱Artificial Intelligence and Security網(wǎng)絡(luò)公開度




書目名稱Artificial Intelligence and Security網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Artificial Intelligence and Security被引頻次




書目名稱Artificial Intelligence and Security被引頻次學(xué)科排名




書目名稱Artificial Intelligence and Security年度引用




書目名稱Artificial Intelligence and Security年度引用學(xué)科排名




書目名稱Artificial Intelligence and Security讀者反饋




書目名稱Artificial Intelligence and Security讀者反饋學(xué)科排名




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發(fā)表于 2025-3-21 21:12:56 | 只看該作者
Die Elemente der FORTRAN-Sprache,TCWTs). Compared with the discrete wavelet transform, DTCWT provides multiple-directions and multiple-scales decomposition to image and also has the fast calculation capability. In the proposed method Multiple DTCWTs is incorporated to get more texture features; compare to Gabor wavelet, DTCWT has l
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地板
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https://doi.org/10.1007/978-3-322-91101-8efore, many learning participants can perform neural network-based deep learning over a combined dataset without revealing the participants’ local data to a central server. However, this privacy-preserving deep learning system is not secure against participant-level attack. We present an effective p
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Erweiterung des Wertebereiches,study. Data collector is such a tool. Compared with the normal data collector, the Topic-focused network data collectors pay more attention to web pages related to pre-set topics. This paper designs and implements a network data collector and in order to improve the search efficiency, this paper use
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https://doi.org/10.1007/978-3-322-93816-9ty of key-points detection will greatly affect the performance of image registration. In this paper, we use the fully convolutional neural network to perform key-points detection and feature extraction on the image, which is applied to the registration. Experiments show that the proposed method achi
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